Abstract

The purpose of this study is to develop a computer-based classifier that automates coral reef assessment from digitized underwater video. We extract low-level color and texture features from coral images to serve as input to a high-level classifier. Low-level features for color were labeled blue, green, yellow/brown/orange, and gray/white, which are described by the normalized chromaticity histograms of these major colors. The color matching capability of these features was determined through a technique called “Histogram Backprojection”. The low-level texture feature marks a region as coarse or fine depending on the gray-level variance of the region.